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👉DeDRM tools for ebooks
😎TOPICS: ``
⭐️STARS：8461, 今日上升数↑:48
👉README：
DeDRM_tools
DeDRM tools for ebooks
This is a repository of all the scripts and other tools for removing DRM from ebooks that I could find, committed in date order as best as I could manage. (Except for the Requiem tools for Apple's iBooks, and Convert LIT for Microsoft's .lit ebooks.)
Mostly it tracks the tools released by Apprentice Alf, athough it also includes the individual tools and their histories from before Alf had a blog.
Users should download the latest zip archive.
Developers might be interested in forking the repository, as it contains unzipped versions of those tools that are zipped to make the changes over time easier to follow.
For the latest Amazon KFX format, users of the calibre plugin should also install the KFX Input p...
👉Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
😎TOPICS: programming,development,design,design-system,system,design-patterns,web,web-application,webapp,python,interview,interview-questions,interview-practice
⭐️STARS：108328, 今日上升数↑:220
👉:art: Diagram as Code for prototyping cloud system architectures
😎TOPICS: diagram,diagram-as-code,drawing,architecture,prototyping
⭐️STARS：9581, 今日上升数↑:233
👉README：
Diagrams
Diagram as Code.
Diagrams lets you draw the cloud system architecture in Python code. It was born for prototyping a new system architecture design without any design tools. You can also describe or visualize the existing system architecture as well. Diagrams currently supports main major providers including: AWS, Azure, GCP, Kubernetes, Alibaba Cloud, Oracle Cloud etc... It also supports On-Premise nodes, SaaS and major Programming frameworks and languages.
Diagram as Code also allows you to track the architecture diagram changes in any version control system.
NOTE: It does not control any actual cloud resources nor does it generate cloud formation or terr...
👉End-to-End Object Detection with Transformers
😎TOPICS: ``
⭐️STARS：4833, 今日上升数↑:11
👉README：
DE⫶TR: End-to-End Object Detection with Transformers
PyTorch training code and pretrained models for DETR (DEtection TRansformer).
We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch.
What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based global loss, which forces unique predictions via bipartite matching, and a Transformer encoder-decoder architecture.
Given a fixed small set of learned object queries, DETR reasons about the relations of the objects and the global image context to directly output the final set of predictions in parallel. Due to this parallel nature, DETR is very fast and efficient.
About the code. We believe that object detection should not be more...
👉A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
😎TOPICS: risk,pricing,risk-management,asset-allocation,finance,valuation,python,derivatives-pricing,numba,bonds,students,fixed-income,derivatives,investment,currency,credit
⭐️STARS：138, 今日上升数↑:38
👉README：
Quick Start Guide
FinancePy can be installed from pip using the command:
pip install financepy
To upgrade an existing installation type:
pip install --upgrade financepy
Using FinancePy in a Jupyter Notebook
Once financepy has been installed, it is easy to get started.
Just download the project and examine the set of Jupyter Notebooks in the notebooks folder.
A pdf manual describing all of the functions can be found in the project directory.
Overview
FinancePy is a python-based library that is currently in beta version. It covers the following functionality:
Valuation and risk models for a wide range of equity, FX, interest rate and credit derivatives.
Although it is written entirely in Python, it can achieve speeds comparable to C++ by using Numba. As a result the user has both the ability to examine the underlying code and the ability to perform pricing and risk at speeds which compare to a library written in C++.
👉:house_with_garden: Open source home automation that puts local control and privacy first
😎TOPICS: python,home-automation,iot,internet-of-things,mqtt,raspberry-pi,asyncio
⭐️STARS：35933, 今日上升数↑:46
👉README：
Home Assistant |Chat Status|
Open source home automation that puts local control and privacy first. Powered by a worldwide community of tinkerers and DIY enthusiasts. Perfect to run on a Raspberry Pi or a local server.
Check out home-assistant.io <https://home-assistant.io>__ for a demo <https://home-assistant.io/demo/>, installation instructions <https://home-assistant.io/getting-started/>, tutorials <https://home-assistant.io/getting-started/automation-2/>__ and documentation <https://home-assistant.io/docs/>__.
|screenshot-states|
Featured integrations
|screenshot-components|
The system is built using a modular approach so support for other devices or actions can be implemented easily. See also the `section on architecture <htt...
We present a new flow-based video completion algorithm. Previous flow completion methods are often unable to retain the sharpness of motion boundaries. Our method first extracts and completes motion edges, and then uses them to guide piecewise-smooth flow completion with sharp edges. Existing methods propagate colors among local flow connections between adjacent frames. However, not all missing regions in a video can be reached in this way because the motion boundaries form impenetrable barriers. Our method alleviates this problem by introducing non-local flow connections to temporally distant frames, enabling propagating video content over motion boundaries. We validate our approach on the DAVIS dataset. Both visual and quantitativ...
👉Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies.
😎TOPICS: quantitative-finance,machine-learning,stock-data,platform,finance,algorithmic-trading,python,investment
⭐️STARS：330, 今日上升数↑:36
👉README：
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment.
With Qlib, you can easily try your ideas to create better Quant investment strategies.
👉A cross-platform network media aggregation application that supports online viewing or listening of live video, HD TV and radio stations. 一个跨平台的网络媒体聚合应用，支持直播视频，高清电视和广播电台的在线观看或收听。
😎TOPICS: cross-platform,media,livestream,live,live-video,hdtv,radio-station
⭐️STARS：559, 今日上升数↑:26
👉A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
😎TOPICS: ``
⭐️STARS：10446, 今日上升数↑:24
Note: If you are looking for the first edition notebooks, check out ageron/handson-ml.
Quick Start
Want to play with these notebooks online without having to install anything?
Use any of the following services.
WARNING: Please be aware that these services provide temporary environments: anything you do will be deleted after a while, so make sure you download any data you care about.
Recommended: open this repository in [Colaboratory](ht...
👉[NeurIPS 2020] This project provides a strong single-stage baseline for Long-Tailed Classification, Detection, and Instance Segmentation (LVIS). It is also a PyTorch implementation of the NeurIPS 2020 paper 'Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect'.
😎TOPICS: ``
⭐️STARS：132, 今日上升数↑:15
👉README：
A Strong Single-Stage Baseline for Long-Tailed Problems
This project provides a strong single-stage baseline for Long-Tailed Classification (under ImageNet-LT, Long-Tailed CIFAR-10/-100 datasets), Detection, and Instance Segmentation (under LVIS dataset). It is also a PyTorch implementation of the NeurIPS 2020 paperLong-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect, which proposes a general solution to remove the bad momentum causal effect for a variety of Long-Tailed Recognition tasks. The codes are organized into three folders:
The classification folder supports long-tailed classification on ImageNet-LT, Long-Tailed CIFAR-10/CIFAR-100 datasets.
The lvis_old folder (deprecated) supports long-tailed object detection and instance segmentation on LVIS V0.5 dataset, which is built on top of mmdet V1.1.
The latest version of long-tailed detection and instance segmentation is under [lvis1.0...
👉A beginner-friendly project to help you in open-source contributions. Made specifically for contributions in HACKTOBERFEST 2020! Algorithms in Python and Machine Learning. Please leave a star ⭐ to support this project! ✨
😎TOPICS: hactoberfest,hactoberfest2020,first-timers,first-pull-request,first-pull-request-and-commit,first-contributions,good-first-issue,open-source,beginner,beginner-friendly,digitalocean,easy-to-use,github,up-for-grabs,machine-learning,python,python3,machinelearning,pr-welcome
⭐️STARS：47, 今日上升数↑:13
👉README：
A beginner friendly project to help you in open source contributions. An attempt to bring all the algorithms together.
The goal of this project is to help the beginners with their contributions in Open Source and bring all the possible algorithms of Machine Learning and Python together. We aim to achieve this collaboratively, so feel free to contribute in any way you want, just make sure to follow the contribution guidelines.
For now, this repo is focused on the beginner friendly contributions in Hacktoberfest 2020.
The open source community provides a great opportunity for aspiring...
👉Repository for the free online book Machine Learning from Scratch (link below!)
😎TOPICS: ``
⭐️STARS：334, 今日上升数↑:41
👉README：
Machine Learning from Scratch
Welcome to the repo for my free online book, "Machine Learning from Scratch".
The book itself can be found here.
(A somewhat ugly version of) the PDF can be found in the book.pdf file above in the master branch. N...
🤩Python随身听-技术精选： /anandpawara/Real_Time_Image_Animation
👉README：
Real time Image Animation
The Project is real time application in opencv using first order model
Steps to setup
Step 1: Create virtual environment
Python version : python v3.7.3 or higher
create virual environment :
pip install virtualenvactivate virtual environment :
virtualenv envStep 2: Activate virtual environment
For windows :
env/Script/activateFor Linux :
source env/bin/activateStep 3 : Install required modules
Install modules :
pip install -r requirements.txtInstall pytorch and torchvision :
pip install torch===1.0.0 torchvision===0.2.1 -f https://download.pytorch.org/whl/cu100/torch_stable.htmlStep 4 : Download cascade file ,weights and model and save in folder named extract
The file is also availible via direct link on Google's Drive:
https://drive.google.com/uc?id=1wCzJP1XJNB04vEORZvPjNz6drkXm5AUK
On Linux machine :
unzip checkpoints.zipIf on windows platfrom unzip checkpoints.zi...
地址：https://github.com/anandpawara/Real_Time_Image_Animation
🤩Python随身听-技术精选： /apprenticeharper/DeDRM_tools
👉README：
DeDRM_tools
DeDRM tools for ebooks
This is a repository of all the scripts and other tools for removing DRM from ebooks that I could find, committed in date order as best as I could manage. (Except for the Requiem tools for Apple's iBooks, and Convert LIT for Microsoft's .lit ebooks.)
Mostly it tracks the tools released by Apprentice Alf, athough it also includes the individual tools and their histories from before Alf had a blog.
Users should download the latest zip archive.
Developers might be interested in forking the repository, as it contains unzipped versions of those tools that are zipped to make the changes over time easier to follow.
For the latest Amazon KFX format, users of the calibre plugin should also install the KFX Input p...
地址：https://github.com/apprenticeharper/DeDRM_tools
🤩Python随身听-技术精选： /donnemartin/system-design-primer
👉README：
*English ∙ 日本語 ∙ 简体中文 ∙ 繁體中文 | العَرَبِيَّة ∙ বাংলা ∙ Português do Brasil ∙ Deutsch ∙ ελληνικά ∙ עברית ∙ Italiano ∙ 한국어 ∙ فارسی ∙ Polski ∙ русский язык ∙ Español ∙ [...
地址：https://github.com/donnemartin/system-design-primer
🤩Python随身听-技术精选： /mingrammer/diagrams
👉README：
Diagrams
Diagram as Code.
Diagrams lets you draw the cloud system architecture in Python code. It was born for prototyping a new system architecture design without any design tools. You can also describe or visualize the existing system architecture as well. Diagrams currently supports main major providers including:
AWS,Azure,GCP,Kubernetes,Alibaba Cloud,Oracle Cloudetc... It also supportsOn-Premisenodes,SaaSand majorProgrammingframeworks and languages.Diagram as Code also allows you to track the architecture diagram changes in any version control system.
地址：https://github.com/mingrammer/diagrams
🤩Python随身听-技术精选： /facebookresearch/detr
👉README：
DE⫶TR: End-to-End Object Detection with Transformers
PyTorch training code and pretrained models for DETR (DEtection TRansformer).
We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch.
What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based global loss, which forces unique predictions via bipartite matching, and a Transformer encoder-decoder architecture.
Given a fixed small set of learned object queries, DETR reasons about the relations of the objects and the global image context to directly output the final set of predictions in parallel. Due to this parallel nature, DETR is very fast and efficient.
About the code. We believe that object detection should not be more...
地址：https://github.com/facebookresearch/detr
🤩Python随身听-技术精选： /google-research/football
👉README：
Google Research Football
This repository contains an RL environment based on open-source game Gameplay
Football.
It was created by the Google Brain team for research purposes.
Useful links:
地址：https://github.com/google-research/football
🤩Python随身听-技术精选： /domokane/FinancePy
👉README：
Quick Start Guide
FinancePy can be installed from pip using the command:
pip install financepyTo upgrade an existing installation type:
pip install --upgrade financepyUsing FinancePy in a Jupyter Notebook
Once financepy has been installed, it is easy to get started.
Just download the project and examine the set of Jupyter Notebooks in the notebooks folder.
A pdf manual describing all of the functions can be found in the project directory.
Overview
FinancePy is a python-based library that is currently in beta version. It covers the following functionality:
Although it is written entirely in Python, it can achieve speeds comparable to C++ by using Numba. As a result the user has both the ability to examine the underlying code and the ability to perform pricing and risk at speeds which compare to a library written in C++.
The target audience for this library includes:
地址：https://github.com/domokane/FinancePy
🤩Python随身听-技术精选： /NVlabs/imaginaire
👉README：
Imaginaire
Docs | License | Installation | Model Zoo
Imaginaire is a pytorch library that contains
optimized implementation of several image and video synthesis methods developed at NVIDIA.
License
Imaginaire is released under NVIDIA Software license.
For commercial use, please consult researchinquiries@nvidia.com
What's inside?
We have a tutorial for each model. Click on the model name, and your browser should take you to the tutorial page for the project.
Supervised Image-to-Image Translation
|Algorithm Name | Feature | Publication |
|:------------------...
地址：https://github.com/NVlabs/imaginaire
🤩Python随身听-技术精选： /rvizzz/rotate
👉README：
rotate
Create recursive image transformation animations
Full demo animation on my Twitter:
https://twitter.com/r_vizzz/status/1311425342310092800?s=20
Older animations:
https://www.youtube.com/watch?v=OXo-uzzD4Js
https://www.reddit.com/r/compsci/comments/izy2kf/rotating_an_image_recursively_one_of_my_favorite/
Usage Instructions
An animation can be generated using the
rotate.pyortransform.pyfile.rotate.py
Arguments:
`python3.7 rotate.py <input_image.png> ...
地址：https://github.com/rvizzz/rotate
🤩Python随身听-技术精选： /home-assistant/core
👉README：
Home Assistant |Chat Status|
Open source home automation that puts local control and privacy first. Powered by a worldwide community of tinkerers and DIY enthusiasts. Perfect to run on a Raspberry Pi or a local server.
Check out
home-assistant.io <https://home-assistant.io>__ fora demo <https://home-assistant.io/demo/>,installation instructions <https://home-assistant.io/getting-started/>,tutorials <https://home-assistant.io/getting-started/automation-2/>__ anddocumentation <https://home-assistant.io/docs/>__.|screenshot-states|
Featured integrations
|screenshot-components|
The system is built using a modular approach so support for other devices or actions can be implemented easily. See also the `section on architecture <htt...
地址：https://github.com/home-assistant/core
🤩Python随身听-技术精选： /ytdl-org/youtube-dl
👉README：
youtube-dl - download videos from youtube.com or other video platforms
INSTALLATION
To install it right away for all UNIX users (Linux, macOS, etc.), type:
If you do not have curl, you can alternatively use a recent wget:
Windows users can download an .exe file and place it in any location on their [PATH](...
地址：https://github.com/ytdl-org/youtube-dl
🤩Python随身听-技术精选： /zdyshine/RTC2020_EfficientSR
👉README：
RTC2020_EfficientSR FZU-CS510 冠军开源方案
比赛链接: https://www.dcjingsai.com/v2/cmptDetail.html?id=409
比赛团队(Team)：FZU-CS510
团队成员：福州大学甘敏教授团队的博士生苏建楠，帝视科技张东阳，澳门大学的博士后研究员陈光永，香港城市大学博士生诸汉炜等
方案分享
代码说明
文件夹的功能如下：
--pretrained-model 存放训练好的模型
--datasets 存放训练数据集和测试集
--results 存在测试的结果图片
--training 存在训练过程中保存的log信息和模...
地址：https://github.com/zdyshine/RTC2020_EfficientSR
🤩Python随身听-技术精选： /vt-vl-lab/FGVC
👉README：
[ECCV 2020] Flow-edge Guided Video Completion
[Paper] [Project Website] [Google Colab (coming soon)]
We present a new flow-based video completion algorithm. Previous flow completion methods are often unable to retain the sharpness of motion boundaries. Our method first extracts and completes motion edges, and then uses them to guide piecewise-smooth flow completion with sharp edges. Existing methods propagate colors among local flow connections between adjacent frames. However, not all missing regions in a video can be reached in this way because the motion boundaries form impenetrable barriers. Our method alleviates this problem by introducing non-local flow connections to temporally distant frames, enabling propagating video content over motion boundaries. We validate our approach on the DAVIS dataset. Both visual and quantitativ...
地址：https://github.com/vt-vl-lab/FGVC
🤩Python随身听-技术精选： /microsoft/qlib
👉README：
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment.
With Qlib, you can easily try your ideas to create better Quant investment strategies.
For more details, please refer to our paper "Qlib: An AI-oriented Quantitative Investment Platform".
地址：https://github.com/microsoft/qlib
🤩Python随身听-技术精选： /parzulpan/real-live
👉README：
RealLive
简体中文 | 繁体中文 | English
桌面端：
使用视频
为什么是它
它解决了什么？
它有什么特性？
它未来会如何？
快速开始
分支说明：
桌面端调试运行：
配置好 Python 开发环境，推荐 Python3.6、Python3.7，其他版本未测试。
首次使用时，Fork 后 Clone 该项目，进入 src/real-live-desktop 桌面端项目文件夹，配置 DebugRun.sh后，然后运行
DebugRun.sh。非首次使用时，...
地址：https://github.com/parzulpan/real-live
🤩Python随身听-技术精选： /apache/airflow
👉README：
Apache Airflow
Apache Airflow (or simply Airflow) is a platform to programmatically author, schedule, and monitor workflows.
When workflows are defined as code, they become more maintainable, vers...
地址：https://github.com/apache/airflow
🤩Python随身听-技术精选： /ageron/handson-ml2
👉README：
Machine Learning Notebooks
This project aims at teaching you the fundamentals of Machine Learning in
python. It contains the example code and solutions to the exercises in the second edition of my O'Reilly book Hands-on Machine Learning with Scikit-Learn, Keras and TensorFlow:
Note: If you are looking for the first edition notebooks, check out ageron/handson-ml.
Quick Start
Want to play with these notebooks online without having to install anything?
Use any of the following services.
WARNING: Please be aware that these services provide temporary environments: anything you do will be deleted after a while, so make sure you download any data you care about.
地址：https://github.com/ageron/handson-ml2
🤩Python随身听-技术精选： /Pierian-Data/Complete-Python-3-Bootcamp
👉README：
Complete-Python-3-Bootcamp
Course Files for Complete Python 3 Bootcamp Course on Udemy
Get it now for ...
地址：https://github.com/Pierian-Data/Complete-Python-3-Bootcamp
🤩Python随身听-技术精选： /KaihuaTang/Long-Tailed-Recognition.pytorch
👉README：
A Strong Single-Stage Baseline for Long-Tailed Problems
This project provides a strong single-stage baseline for Long-Tailed Classification (under ImageNet-LT, Long-Tailed CIFAR-10/-100 datasets), Detection, and Instance Segmentation (under LVIS dataset). It is also a PyTorch implementation of the NeurIPS 2020 paper Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect, which proposes a general solution to remove the bad momentum causal effect for a variety of Long-Tailed Recognition tasks. The codes are organized into three folders:
地址：https://github.com/KaihuaTang/Long-Tailed-Recognition.pytorch
🤩Python随身听-技术精选： /geekquad/AlgoBook
👉README：
A beginner friendly project to help you in open source contributions. An attempt to bring all the algorithms together.Please see the Contributing Guidelines .
Join the community on Slack.
Overview
The goal of this project is to help the beginners with their contributions in Open Source and bring all the possible algorithms of Machine Learning and Python together. We aim to achieve this collaboratively, so feel free to contribute in any way you want, just make sure to follow the contribution guidelines.
For now, this repo is focused on the beginner friendly contributions in Hacktoberfest 2020.
The open source community provides a great opportunity for aspiring...
地址：https://github.com/geekquad/AlgoBook
🤩Python随身听-技术精选： /Mikoto10032/DeepLearning
👉README：
DeepLearning Tutorial
一. 入门资料
完备的 AI 学习路线，最详细的中英文资源整理 ⭐
AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NL
Machine-Learning
数学基础
机器学习基础
快速入门
地址：https://github.com/Mikoto10032/DeepLearning
🤩Python随身听-技术精选： /dafriedman97/mlbook
👉README：
Machine Learning from Scratch
Welcome to the repo for my free online book, "Machine Learning from Scratch".
The book itself can be found here.
(A somewhat ugly version of) the PDF can be found in the book.pdf file above in the
masterbranch. N...地址：https://github.com/dafriedman97/mlbook
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